Merge branch 'main' of https://huggingface.co/datasets/MITLL/LADI-v2-dataset

README.md

@@ -83,15 +83,31 @@ A single example in the v2a dataset looks like this:
 
 Examples in the v1 datasets are analogous, with classes drawn from their respective tasks (infrastructure and damage).
 ## Using the Dataset
-### Downloading the Dataset
-You can download the dataset by loading it with `download_ladi=True`, which fetches the compressed data from an s3 bucket and extracts it into your filesystem:
+### Default Configuration
+The `main` branch of the dataset will load the `v2a` label set with images resized to fit within 1800x1200. For most use cases, this should be sufficient.
+
+```python
+from datasets import load_dataset
+ds = load_dataset("MITLL/LADI-v2-dataset")
+```
+
+### Advanced usage
+If you need access to the full resolution images, the v2 label set, or the v1 dataset, you should load from the `script` revision. 
+This will use a custom dataset loader script, which will require you to set `trust_remote_code=True`.
+
+The available configurations for the script are: `v2`, `v2a`, `v2_resized`, `v2a_resized`, `v1_damage`, `v1_infra`. 
+
+You can download the dataset by loading it with `download_ladi=True`, which fetches the compressed data from an s3 bucket and extracts it into your filesystem at `base_dir`:
 
 ```python
 from datasets import load_dataset
 
 ds = load_dataset("MITLL/LADI-v2-dataset", "v2a_resized",
-                streaming=True, download_ladi=True,
-                base_dir='./ladi_dataset', trust_remote_code=True)
+                revision="script",
+                streaming=True,
+                download_ladi=True,
+                base_dir='./ladi_dataset',
+                trust_remote_code=True)
 ```
 
 You can browse the bucket here: [https://ladi.s3.amazonaws.com/index.html](https://ladi.s3.amazonaws.com/index.html). Note that the `v2_resized` dataset is the same as the `v2` dataset, but with lower-resolution images (1800x1200 px). We expect that these images are still more than large enough to support most tasks, and encourage you to use the v2_resized and v2a_resized datasets when possible as the download is about 45x smaller. We try not to download images you don't need, so this will only fetch the v2_resized images, leaving v1 and v2 alone.
@@ -102,7 +118,9 @@ We intend for this dataset to be used mostly in streaming mode from individual f
 from datasets import load_dataset
 
 ds = load_dataset("MITLL/LADI-v2-dataset", "v2a_resized",
-                streaming=True, base_dir='./ladi_dataset', 
+                revision="script",
+                streaming=True,
+                base_dir='./ladi_dataset', 
                 trust_remote_code=True)
 ```